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DOI Partnership: Distinguishing Between Human and Natural Causes of Changes in Nearshore Ecosystems Using Long-Term Data from DOI Monitoring Programs

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DOI Partnership: Distinguishing Between Human and Natural Causes of Changes in Nearshore Ecosystems Using Long-Term Data from DOI Monitoring Programs OCS Study BOEM 2019-063 DOI Partnership: Distinguishing between Human and Natural Causes of Changes in Nearshore Ecosystems Using Long-term Data from DOI Monitoring Programs US Department of the Interior Bureau of Ocean Energy Management Pacific OCS Region OCS Study BOEM 2019-063 DOI Partnership: Distinguishing between Human and Natural Causes of Changes in Nearshore Ecosystems Using Long-term Data from DOI Monitoring Programs September 2019 Authors: Daniel C. Reed, Andrew Rassweiler, and Kevin D. Lafferty Prepared under Cooperative Agreement M11AC00012 By Marine Science Institute University of California, Santa Barbara Santa Barbara, CA 93106 US Department of the Interior Bureau of Ocean Energy Management Pacific OCS Region DISCLAIMER Study collaboration and funding were provided by the US Department of the Interior, Bureau of Ocean Energy Management (BOEM), Environmental Studies Program, Washington, DC, under Agreement Number M11AC00012. This report has been technically reviewed by BOEM, and it has been approved for publication. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the opinions or policies of the US Government, nor does mention of trade names or commercial products constitute endorsement or recommendation for use. REPORT AVAILABILITY To download a PDF file of this report, go to the US Department of the Interior, Bureau of Ocean Energy Management Data and Information Systems webpage (https://www.boem.gov/Environmental-Studies- EnvData/), click on the link for the Environmental Studies Program Information System (ESPIS), and search on 2019-063. CITATION Reed DC, Rassweiler A, Lafferty KD. 2019. DOI Partnership: Distinguishing between human and natural causes of changes in nearshore ecosystems using long-term data from DOI monitoring programs. Camarillo (CA): US Department of the Interior, Bureau of Ocean Energy Management. OCS Study BOEM 2019-063. 117 p. ABOUT THE COVER Ronald H. McPeak, Underwater and Coastal California Photographs, 1965-1999 (Mss 292) Department of Special Collections, Davidson Library, University of California, Santa Barbara. © Regents of the University of California. Licensed for non-commercial use under a Creative Commons Attribution- NonCommercial 3.0 Unported License. ACKNOWLEDGMENTS This research relied on data collected by the National Park Service, the United States Geological Survey, the Partnership for Interdisciplinary Studies of Coastal Oceans, and the Santa Barbara Coastal Long Term Ecological Research project. We thank these programs and all the staff and volunteers involved in collecting and assembling the data. We also think the Santa Barbara Channel - Marine Biodiversity Observing Network project for assistance with data synthesis. We thank the many scientists who participated in some aspect of this work including Donna Schroeder, Jim Estes, David Kushner, Mike Kenner, Josh Sprague, Dan Okamoto, Mark Novak, Tim Tinker, Jenn Caselle, Ally Dubel, Li Kui, Shannon Harrer, Jacob Staines, and Katie Davis. Contents List of Abbreviations and Acronyms ............................................................................................................... ii 1 Executive Summary ................................................................................................................................ 1 2 Project Description.................................................................................................................................. 2 2.1 Introduction .................................................................................................................................... 2 2.2 Data acquisition, documentation and publication of DOI data sets ............................................... 3 2.3 Integrating DOI data sets with data from different monitoring programs to facilitate analyses across a broad range of temporal, spatial and taxonomic scales ................................................. 4 2.4 Patterns of spatial and temporal variability in kelp forest communities and environmental and anthropogenic factors that drive them .................................................................................... 6 2.5 Integration with other BOEM-funded studies................................................................................. 7 3 References ............................................................................................................................................. 9 Appendix A: A multi-decade time series of kelp forest community structure at the California Channel Islands .................................................................................................................................... 10 Appendix B: A multi-decade time series of kelp forest community structure at San Nicolas Island, California ................................................................................................................................ 36 Appendix C: DOI partnership integrated data package - Metadata ............................................................ 53 Appendix D: Detecting human impacts in a highly variable ecosystem using long-term monitoring data .. 71 Appendix E: Scale-specific drivers of kelp forest communities ................................................................... 93 i List of Abbreviations and Acronyms ASCII American Standard Code for Information Interchange BACI Before-After-Control-Impact BOEM Bureau of Ocean Energy Management BON Biodiversity Observation Network BOT Bottom CDIP Coastal Data Information Program CAN Canopy CINP Channel Islands National Park CNMD Canopy-Midwater dbMEM distance-based Moran’s Eigenvector Maps DOI US Department of the Interior ESP Environmental Studies Program ESPIS Environmental Studies Program Information System FUL Full KFM Kelp Forest Monitoring program LTER Long Term Ecological Research program OCS Outer Continental Shelf PCNM Principal Coordinates analysis of Neighborhood Matrices PDF Probability Density Function PISCO Partnership for Interdisciplinary Studies of Coastal Oceans RDA Redundancy Analysis RDFC Random Diver Fish Counts ROMS Regional Ocean Modelling System RPC Random Point Contact SCB Southern California Bight SNI San Nicolas Island monitoring program SST Sea Surface Temperature UPC Uniform Point Contact USFWS US Fish and Wildlife Service USGS United States Geological Survey ii 1 Executive Summary Monitoring and predicting the potential impacts of outer continental shelf (OCS) energy production on nearshore ecosystems requires an ability to distinguish between changes caused by natural processes and those caused by human activities. The ability to distinguish such changes in turn requires long-term, spatially extensive data to describe natural patterns of temporal and spatial variation in species abundances and the environmental factors that influence them. This is particularly true for giant kelp forests, which are highly productive and diverse ecosystems in temperate regions that fluctuate greatly in space and time. These systems are highly valued for the milieu of goods and services they provide to society and there is general interest in minimizing anthropogenic activities that adversely affect them. The purpose of this project was to partner with agencies in the Department of the Interior (DOI) to document, integrate and analyze data produced from long-term kelp forest monitoring programs to improve our understanding of the causes and consequences of change in these iconic ecosystems. The primary objectives in this collaborative partnership were fourfold: (1) Work with two Department of the Interior agencies to assimilate, document and published their long-term (30 + years) data sets pertaining to kelp forest community structure at the northern Channel Islands and San Nicolas Island; (2) Expand the spatial scope of these data sets by integrating them with other long-term kelp forest monitoring programs in the region and with appropriately temporally and spatially scaled environmental data to produce a data resource with unrivaled temporal, spatial and taxonomic scope; (3) Analyze integrated data sets across multiple spatial and temporal scales to ascertain patterns of variation in population and community dynamics and to identify key environmental and anthropogenic factors that drive them; (4) Use the fully integrated data sets to collaborate with BOEM partners and other BOEM- funded programs on issues relevant to BOEM’s mission The value of this project to BOEM lies in its ability to assist managers in detecting and evaluating possible impacts from offshore energy activities, and in developing options to mitigate these impacts. In addition, identification of patterns in these data sets will aid in predicting potential ecosystem impacts due to climate change and advancing adaptive management, both of which are goals central to DOI stewardship responsibilities and trust resources. One lesson of this project is that the time and expense necessary to make data visible, easy to use and easy to combine with other data should not be underestimated, but that such efforts can have very positive results on how widely that data is accessed and used. When long term ecological monitoring continues for decades, there is a danger either that too little metadata is assembled, preventing interpretation of the data, or that so much metadata is assembled that the volume of information becomes a barrier to understanding what was done. The process of publishing data sets
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